简介：Aneuralnetwork(NN)isapowerfultoolforapproximatingboundedcontinuousfunctionsinmachinelearning.TheNNprovidesaframeworkfornumericallysolvingordinarydifferentialequations(ODEs)andpartialdifferentialequations(PDEs)combinedwiththeautomaticdifferentiation(AD)technique.Inthiswork,weexploretheuseofNNforthefunctionapproximationandproposeauniversalsolverforODEsandPDEs.ThesolveristestedforinitialvalueproblemsandboundaryvalueproblemsofODEs,andtheresultsexhibithighaccuracyfornotonlytheunknownfunctionsbutalsotheirderivatives.ThesamestrategycanbeusedtoconstructaPDEsolverbasedoncollocationpointsinsteadofamesh,whichistestedwiththeBurgersequationandtheheatequation(i.e.,theLaplaceequation).